The development of complementary DNA (“cDNA”) microarray technology has provided scientists with a powerful analytical tool for genetic research (M. Schena, D. Shalon, R. W. Davis, and P. O. Brown, “Quantitative monitoring of gene expression patterns with a complementary DNA microarray,” Science, 270[5235], 467–70, 1995). For example, a researcher can compare expression levels in two samples of biological material for thousands of genes simultaneously via a single microarray experiment. Application of automation to the microarray experiment processes further enhances researchers' ability to perform numerous experiments in less time. Consequently, an emerging challenge in the field of genetics is finding new and useful ways to analyze the large body of data produced by such microarray experiments.